Staff Engineer - Backend & AI Systems

We are looking for a Staff Engineer with deep backend engineering experience who has started integrating AI into production systems. Backend is your foundation — 7+ years owning microservices, APIs, and distributed systems at scale. AI is your evolution — you have shipped at least one LLM-powered feature in production, and you understand where the technology is taking the industry.

Key Responsibilities:

Backend Architecture & Engineering:

• Own the technical architecture of Vezeeta’s core backend systems — booking, pharmacy, CRM, and patient management — ensuring they are scalable, fault-tolerant, and production-ready.
• Collaborate closely with product and business stakeholders to translate requirements into clear, actionable technical directions.
• Design and govern microservices architecture: service boundaries, communication patterns, data models, and reliability standards.
• Set and enforce backend engineering standards across the team: code quality, design patterns, testing strategy, and CI/CD practices.
• Solve cross-cutting architectural problems that require someone with enough seniority to make decisions affecting multiple teams.
• Own backend performance: query optimisation, caching strategies, latency targets, and system observability.

• Own the integration layer between AI capabilities and Vezeeta’s backend services — how LLMs, agents, and RAG pipelines plug into booking, pharmacy, and patient systems.
• Own the technical delivery roadmap for AI features — from design through deployment, monitoring, and iteration.
• Build production-grade AI integrations that are reliable, observable, and maintainable — treating AI as an engineering discipline, not a research experiment.
• Establish AI engineering best practices for the team: how to integrate LLMs reliably, how to monitor AI systems in production, how to evaluate quality and manage cost.
• Evaluate and recommend AI frameworks and tools that make practical sense for Vezeeta’s specific needs.

• Serve as the technical reference across engineering squads — the person others escalate hard architectural decisions to.
• Mentor senior engineers and raise the technical bar through code reviews, architecture sessions, and
• Knowledge sharing.
• Translate product and business requirements into clear technical direction and system designs.
• Partner with the Tech VP on architectural strategy, technical trade-offs, and the engineering roadmap.

Backend Engineering — Non-Negotiable:

• 7+ years of backend engineering experience with strong ownership of production systems at scale.
• Proficiency in C#/.NET and/or Python — building APIs, microservices, and backend services that real
• users depend on.
• Deep understanding of microservices architecture, distributed systems, and event-driven design.
• Strong database expertise: SQL Server, PostgreSQL, or MySQL — schema design, query optimisation, and
• indexing.
• Hands-on production experience with Docker and Kubernetes.
• Experience with cloud platforms — AWS preferred (Lambda, ECS, SQS, SNS, S3, RDS).
• Confirmed technical leadership experience: setting standards, reviewing architecture, mentoring
• engineers.

• Has shipped at least one LLM-powered feature, AI agent, or RAG pipeline in a production environment — not a demo, not a course project.
• Familiar with at least one AI integration framework: LangChain, LangGraph, Semantic Kernel, or equivalent.
• Basic understanding of RAG architecture and vector databases.
• Comfortable making an LLM API call from a backend service and handling the reliability, latency, and cost implications.
• Curious about AI and staying current — experimenting, not just reading.

• Communicates technical complexity clearly to both engineers and non-technical stakeholders.
• Opinionated about engineering quality but pragmatic about delivery.
• Self-directed and proactive — identifies problems before they become incidents.
• Comfortable with ambiguity and fast-moving environments.

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• Demonstrated production experience is weighted more than formal credentials.

• Own the backend architecture of a healthcare platform serving millions of patients across the MENA region.
• Be the technical reference for the engineering team — cross-team influence without becoming a people manager.
• Build the bridge between Vezeeta’s proven backend infrastructure and the AI layer that will define its next chapter.
• Direct partnership with the Tech VP on architectural decisions and engineering strategy.
• A clear growth path toward Principal Engineer or Head of Engineering as the platform and team scale.